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Conference on sensor fusion - architectures, algorithms, and applications

作者： Zachary, JM Iyengar, SS Louisiana State Univ. (United States)

ISBN: (纸本)081942482X

Traditional surface reconstruction techniques have focused exclusively on contour sections in one anatomical direction. However, in certain medical situations, such as in presurgical planning and radiation treatment, medical scans are taking of the patient in three orthogonal directions to better localize pathologies. fusion techniques must be used to register this data with respect to a surface fitting method. We explore the issues involved in fusing data from ellipsoid anatomy, such as the brain, heart, and major organs. The output of the fusion process is a set of data points which are correlated to one another to represent the surface of a single object. This data network is then used as input to a surface fitting algorithm which depends on two sampling metrics which we derive. The solution to this problem is important in presurgical planning, radiation treatment, and telemedical systems.

关键词： data fusion contour reconstruction surface reconstruction scattered data

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IMAGE-BASED TARGET TRACKING - fusion ARCHITECTURE AND sensor MANAGEMENT 2

IMAGE-BASED TARGET TRACKING - FUSION ARCHITECTURE AND SENSOR...

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CONF ON SIGNAL PROCESSING, sensor fusion, AND TARGET RECOGNITION 2

作者： HERSEN, B LALO, A LANEUVILLE, D MARITON, M MATRA MS2i (France)

ISBN: (纸本)0819411914

Following the acceptance of the linear Gauss Markov paradigm pioneered by Kalman, the engineering practice for the design of target tracking applications had been maturing over the last two decades. In recent years however two emerging facts have called for a renewed attention from the research community: (1) the generalization of multiple sensor architectures, motivated by higher requirements in terms of target description and robustness to electronic warfare, and (2) the availability of affordable imaging sensors, following progress in infrared detectors technology. The purpose of this communication is to report on some recent work addressing the issues raised by these two new aspects of tracking application design. Ideas are illustrated using an air defense scenario.

关键词： sensors Optical sensors Detection and tracking algorithms Environmental sensing Image processing Defense and security Image fusion Image sensors Imaging systems sensor fusion

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ELIPS: toward a sensor fusion processor on a chip

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Proceedings of SPIE - The International Society for Optical Engineering 1999年 3719卷 209-219页

作者： Daud, Taher Stoica, Adrian Thomas, Tyson Li, Wei-te Fabunmi, James California Inst of Technology Pasadena United States

The paper presents the concept and initial tests from the hardware implementation of a low-power, high-speed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) processor is developed to seamlessly combine rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor in compact low power VLSI. The first demonstration of the ELIPS concept targets interceptor functionality; other applications, mainly in robotics and autonomous systems are considered for the future. The main assumption behind ELIPS is that fuzzy, rule-based and neural forms of computation can serve as the main primitives of an 'intelligent' processor. Thus, in the same way classic processors are designed to optimize the hardware implementation of a set of fundamental operations, ELIPS is developed as an efficient implementation of computational intelligence primitives, and relies on a set of fuzzy set, fuzzy inference and neural modules, built in programmable analog hardware. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Following software demonstrations on several interceptor data, three important ELIPS building blocks (a fuzzy set preprocessor, a rule-based fuzzy system and a neural network) have been fabricated in analog VLSI hardware and demonstrated microsecond-processing times.

关键词： Computer hardware

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Data fusion for Intelligent Crowd Monitoring and Management Systems: A Survey

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IEEE ACCESS 2021年 9卷 47069-47083页

作者： Li, Xianzhi Yu, Qiao Alzahrani, Bander Barnawi, Ahmed Alhindi, Ahmed Alghazzawi, Daniyal Miao, Yiming Chinese Univ Hong Kong CUHK Dept Comp Sci & Engn Hong Kong Peoples R China Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Peoples R China King Abdulaziz Univ Fac Comp & Informat Technol Jeddah Saudi Arabia Umm Al Qura Univ Dept Comp Sci Mecca Saudi Arabia

Intelligent Crowd Monitoring and Management Systems (ICMMSs) have become effective resources for strengthening safety and security along with enhancing early-warning capabilities to manage emergencies in crowded situations of smart cities and massive gatherings events. The main advantage of such systems is their ability to detect multiple features associated with the crowd gathering, as they enable multi-source sensors, multi-modal data, and powerful intelligent and analytical methods. Unlike traditional crowd monitoring systems, which make use of simplex forms of different data types, data and information associated with crowded scenarios can be collected, fused, processed and analyzed in large quantities for accurate global assessment and enhanced decision making processes in an ICMMS. Therefore, data fusion is introduced as an enabler to decrease data quantity, reduce data dimensions, and improve data quality. In this paper, we first survey the literature on data fusion application in crowd monitoring systems as we are developing a state-of-the-art ICMMS with data fusion as a major platform enabler. Next, we discuss some popular data fusion architectures and classifications from different perspectives. Based on this, we propose a multi-sensor, multi-modal, and dimensional ICMMS architecture based on data fusion. Then, we identify the data fusion processes in the ICMMS and classify them into sensor fusion, feature-based data fusion, and decision fusion. Relevant algorithms, applications and examples of three classes are elaborated. Finally, future data fusion research directions are discussed.

关键词： Data integration Monitoring sensor fusion sensors Cameras Intelligent sensors Temperature sensors Autonomous system crowd monitoring data fusion decision fusion sensor fusion

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The system parameter fusion principle and its application to fuzzy pattern recognition

The system parameter fusion principle and its application to...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms and applications 2003

作者： Pu, QG Univ Sci & Technol Ctr Comp Suzhou 215011 Jiangsu Peoples R China

ISBN: (纸本)0819449598

Modern technology provides a great amount of information. In computer monitoring systems or computer control systems, especially real-time expert systems, in order to have the situation in hand, we need one or two parameters to express the quality and/or security of the whole system. This paper presents a principle for synthesizing measurements of multiple system parameters into a single parameter and its application to fuzzy pattern recognition.

关键词： sensor fusion fuzzy pattern recognition computer monitoring systems computer control systems realtime expert systems

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Proceedings of SPIE: Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2003

Proceedings of SPIE: Multisensor, Multisource Information Fu...

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Multisensor. Multisource Information fusion: architectures, algorithms, and applications 2003

This Volume 5099 of the conference proceedings contains 45 papers. Topics discussed include classification and decision fusion, image level fusion, approximate reasoning methodologies, estimation and tracking, fusion methodologies, evolving concepts and methodologies, architectures and related topics, industrial, medical and speech applications, defense applications, sensor/resource management and related topics.

关键词： sensor data fusion

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Better-than-the-Best fusion Algorithm with Application in Human Activity Recognition

Better-than-the-Best Fusion Algorithm with Application in Hu...

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Conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Najjar, Nayeff Gupta, Shalabh Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)9781628416145

This paper introduces the Better-than-the-Best fusion (BB-Fus) algorithm. The BB-Fus algorithm is a simple and effective information fusion algorithm that combines the information from different sources (be it sensors, features or classifiers) to improve the Correct Classification Rate (CCR). It can be observed that in most classification problems, different sensors or features might have different classification accuracies in separating different classes. Therefore, this paper constructs an optimal decision tree that isolates one class at a time with the best sensor to separate that particular class. The paper shows that the decision tree improves the overall CCR as compared to the use of any single sensor or feature for any 3-class classification problem. The efficiency of the BB-Fus algorithm is validated on the Opportunity data set to solve the human activity recognition problem where a set of 56 sensors (including a localization system, accelerometers, inertial measurement units and magnetic sensors mounted on various body parts;besides, accelerometers and gyroscopes mounted on different objects) are used. The CCR resulting from the BB-Fus algorithm is 96% while the best sensor achieved 94% CCR.

关键词： sensor fusion Information fusion Human Activity Recognition BB-Fus Decision Trees

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MathWeb™:: A concurrent image analysis tool suite for multi-spectral data fusion

MathWeb™:: A concurrent image analysis tool suite for multi...

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Conference on sensor fusion - architectures, algorithms, and applications iiI

作者： Achalakul, T Haaland, PD Taylor, S Syracuse Univ Dept Elect Engn & Comp Sci Syracuse NY 13244 USA

ISBN: (纸本)0819431931

This paper describes a preliminary approach to the fusion of multi-spectral image data for the analysis of cervical cancer. The long-term goal of this research is to define spectral signatures and automatically detect cancer cell structures. The approach combines a multi-spectral microscope with an image analysis tool suite, MathWeb. The tool suite incorporates a concurrent Principal Component Transform (PCT) that is used to fuse the multi-spectral data. This paper describes the general approach and the concurrent PCT algorithm. The algorithm is evaluated from both the perspective of image quality and performance scalability.

关键词： concurrent computing image fusion principal component transform spectral signature

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Bayesian approach to sensor fusion in a multi-sensor land mine detection system

Bayesian approach to sensor fusion in a multi-sensor land mi...

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Conference on sensor fusion - architectures, algorithms, and applications VI

作者： Erickson, D Kacelenga, R Palmer, D Gen Dynam Canada Ltd Calgary AB T2E 8P2 Canada

ISBN: (纸本)0819444812

In the present study, the investigation by General Dynamics Canada, formerly Computing Devices Canada, into Bayesian Inference shows improved sensor fusion of multiple scanning sensors in the detection of buried anti-tank (AT) mines. This algorithm uses statistical data taken from trials and constructs conditional probabilities for individual sensors in order to better discern landmines.

关键词： landmine detection Baye's rule Bayesian inference conditional probability minimum metal detector ground penetrating radar forward-looking infrared multi-sensor fusion

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sensor array calibration via tracking with the extended Kalman filter

Sensor array calibration via tracking with the extended Kalm...

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Conference on sensor fusion - architectures, algorithms, and applications V

作者： Cevher, V McClellan, JH Georgia Tech Sch ECE CSIP Atlanta GA 30332 USA

ISBN: (纸本)0819440809

Starting with a randomly distributed sensor array with unknown sensor orientations, array calibration is needed before target localization and tracking can be performed using classical triangulation methods. In this paper, we assume that the sensors are only capable of accurate direction of arrival (DOA) estimation. The calibration problem cannot be completely solved given the DOA estimates alone, since the problem is not only rotationally symmetric but also includes a range ambiguity. Our approach to calibration is based on tracking a single target moving at a constant velocity. In this case, the sensor array can be calibrated from target tracks generated by an extended Kalman filter (EKF) at each sensor. A simple algorithm based on geometrical matching of similar triangles will align the seperate tracks and determine the sensor positions and orientations relative to a reference sensor. Computer simulations show that the algorithm performs well even with noisy DOA estimates at the sensors.

关键词： tracking array calibration extended Kalman filter DOA

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